Triple
T67242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Légion d'honneur |
E1340
|
entity |
| Predicate | hasFiveClassStructure |
P4203
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [Légion d'honneur, hasFiveClassStructure, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFiveClassStructure Context triple: [Légion d'honneur, hasFiveClassStructure, true]
-
A.
hasStructureType
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
B.
hasOrganizationalStructure
Indicates that an entity possesses a defined internal arrangement of roles, responsibilities, and relationships that determine how it is organized and operates.
-
C.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
-
D.
hasForm
Indicates that one entity possesses, exhibits, or is characterized by a particular shape, structure, or configuration.
-
E.
hasCheckAndBalanceFunction
Indicates that one entity performs a checking or limiting role on another entity’s powers, providing oversight and balance within a system.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2509a1c088190b4afa3045455709a |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.